2 papers
cs.AI2026
A.X K2 Technical Report
Cheolseung Baek, Dhammiko Arya, Eunki Kim +40
We introduce A.X K2, a 688B-parameter Mixture-of-Experts (MoE) language model trained from scratch as a high-performance foundation for \emph{agentic} applications. Trained on appr…
cs.CL2025
Prompt-based Depth Pruning of Large Language Models
Juyun Wee, Minjae Park, Jaeho Lee
Depth pruning aims to reduce the inference cost of a large language model without any hardware-specific complications, by simply removing several less important transformer blocks.…